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  1. 601

    Effects of distant biofield energy healing on adults associated with psychological and mental health-related symptoms: a randomized, placebo-controlled, double-blind study by Mahendra Kumar Trivedi, Alice Branton, Dahryn Trivedi, Sambhu Mondal, Snehasis Jana

    Published 2024-08-01
    “… # Results Perceived psychological symptoms/scores (fatigue/tiredness, sleep disturbances, stress, cognitive impairment, loss of memory, mental restlessness, emotional trauma, anxiety, depression, confusion, financial crises and dissatisfaction, low libido, motivation, confidence, lack of perception, relationship, and social behaviors, etc.) were significantly (p <.0001) improved in biofield intervention group compared to the naïve control and sham control groups. Besides, biofield intervention did not show any study-related adverse effects in all three groups throughout the trial…”
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  2. 602

    Comparison of growth, relative abundance, and diet of three sympatric Hemiandrus ground wētā (Orthoptera, Anostostomatidae) in a New Zealand Forest by Nyasha Chikwature, Mary Morgan-Richards, Jessica Vereijssen, Steven A. Trewick

    Published 2025-01-01
    “…Using hind leg dimensions, we categorized each female H. electra specimen using naïve Gaussian mixture model clustering, which identified five size clusters (putatively corresponding to instars). …”
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  3. 603

    Regulatory T Cells in the Immunodiagnosis and Outcome of Kidney Allograft Rejection by O. Franzese, A. Mascali, A. Capria, V. Castagnola, L. Paganizza, N. Di Daniele

    Published 2013-01-01
    “…Cellular rejection develops when donor alloantigens, presented by antigen-presenting cells (APCs) through class I or class II HLA molecules, activate the immune response against the allograft, resulting in activation of naive T cells that differentiate into subsets including cytotoxic CD8+ and helper CD4+ T cells type 1 (TH1) and TH2 cells or into cytoprotective immunoregulatory T cells (Tregs). …”
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  4. 604

    METAMODERNISM MAN IN THE WORLDVIEW DIMENSION OF NEW CULTURAL PARADIGM by Y. O. Shabanova

    Published 2020-12-01
    “…Proceeding from this, the fate of a metamodernism man is determined in pursuit of the endlessly receding horizons of the anthropology of incompleteness, which is carried out through post-irony, naive sincerity, optimistic openness to the world.…”
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  5. 605

    Makine öğrenmesi yöntemleriyle müşteri kaybı analizi by Murat Fatih Tuna, Oğuz Kaynar, Yasin Görmez, Mehmet Ali Deveci

    Published 2017-05-01
    “…Bu çalışmada, telekomünikasyon sektöründe müşteri kaybını tahmin etmek için, Destek Vektör Makineleri (DVM), Yapay Sinir Ağları (YSA) ve Naive Bayes (NB) gibi çeşitli sınıflama yöntemleri yardımıyla bir analiz gerçekleştirilmiştir. …”
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  6. 606

    CD4+ T Cells Mediate Dendritic Cell Licensing to Promote Multi‐Antigen Anti‐Leukemic Immune Response by Luis Gil‐de‐Gómez, Joseph J. Mattei, Jessica H. Lee, Stephan A. Grupp, Gregor S. D. Reid, Alix E. Seif

    Published 2025-01-01
    “…In vitro assays confirm the ability of CD4+ T cells from leukemia‐responsive mice to promote robust maturation of naïve bone marrow DC in the presence of non‐immunogenic leukemia antigens. …”
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  7. 607

    Gamma-Glutamyl Transpeptidase-to-Platelet Ratio Predicts Significant Liver Fibrosis of Chronic Hepatitis B Patients in China by Tianyi Ren, Huan Wang, Ruihong Wu, Junqi Niu

    Published 2017-01-01
    “…A total of 160 treatment-naïve CHB patients who underwent liver biopsy were enrolled in our study, and we assessed the diagnostic accuracies of GPR, aspartate transaminase-to-platelet ratio index (APRI), and the fibrosis index based on 4 factors (FIB-4) in them. …”
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  8. 608

    Advancements in Predictive Analytics: Machine Learning Approaches to Estimating Length of Stay and Mortality in Sepsis by Houssem Ben Khalfallah, Mariem Jelassi, Jacques Demongeot, Narjès Bellamine Ben Saoud

    Published 2025-01-01
    “…The results demonstrate that Random Forest and Extra Trees achieve high accuracy for LOS prediction, while Gradient Boosting and Bernoulli Naïve Bayes effectively predict mortality. Feature importance analysis identified ICU stay duration (ICU_DAYS_OBS) as the most influential predictor for both outcomes, alongside vital signs, white blood cell counts, and lactic acid levels. …”
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  9. 609

    Assessing spacer acquisition rates in E. coli type I-E CRISPR arrays by Luke J. Peach, Haoyun Zhang, Brian P. Weaver, James Q. Boedicker, James Q. Boedicker

    Published 2025-01-01
    “…The rates at which spacers integrate into native arrays within bacterial populations have not been quantified. Here, we measure naïve spacer acquisition rates in Escherichia coli Type I-E CRISPR, identify factors that affect these rates, and model this process fundamental to CRISPR/Cas defense. …”
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  10. 610

    Crude Ethanol Extract of Diospyros mespiliformis Hochst. ex A. DC. Ebenaceae Leaf and Its Fractions Ameliorate Hyperglycemia and Hyperlipidemia in Alloxan-induced Diabetic Rats by Mubarak Muhammad Dahiru, Neksumi Musa

    Published 2024-12-01
    “…All the extract-treated groups exhibited a significant increase (p < 0.05) in urea and creatinine levels than the naïve control group (6.94 ± 0.20 mM/L). Moreover, the Na+ remained significantly (p > 0.05) unchanged while the K+ level was significantly (p < 0.05) increased for the treatment groups. …”
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  11. 611

    Multiscale Time-Frequency Sparse Transformer Based on Partly Interpretable Method for Bearing Fault Diagnosis by Shouquan Che, Jianfeng Lu, Congwang Bao, Caihong Zhang, Yongzhi Liu

    Published 2023-01-01
    “…Second, a sparse self-attention mechanism is designed to eliminate the feature mapping defect in naive self-attention mechanism. Then, the novel encoder-decoder structure is presented, the multiple encoders are employed to extract the hidden feature of different time-frequency sequences obtained by STFT with different window widths, and the decoder is used to remap the deep information and connect to the classifier for discriminating fault types. …”
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  12. 612

    Analysis of the aqueous humor before and after the administration of faricimab in patients with nAMD by Ryo Nonogaki, Hikaru Ota, Jun Takeuchi, Yuyako Nakano, Ai Fujita Sajiki, Takahito Todoroki, Koichi Nakamura, Hiroki Kaneko, Koji M. Nishiguchi

    Published 2024-12-01
    “…Abstract This study aimed to evaluate the changes in cytokine levels in the aqueous humor and factors of treatment resistance following intravitreal faricimab injection in treatment-naïve patients with neovascular age-related macular degeneration. …”
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  13. 613

    The Anticonvulsant Enaminone E139 Attenuates Paclitaxel-Induced Neuropathic Pain in Rodents by Dhandapani Thangamani, Ivan Ogheneochuko Edafiogho, Willias Masocha

    Published 2013-01-01
    “…Administration of E139 (10–40 mg/kg) produced antinociceptive activity against thermal nociception in naïve mice. Treatment with E139, amitriptyline, or gabapentin reduced paclitaxel-induced thermal hyperalgesia. …”
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  14. 614

    Randomized Crossover Study Showing Nurse-Led Same Day Review Replacing Next Day Review in Uneventful Phacoemulsification to Be Safe and Efficacious by Jennifer W. H. Shum, Janice J. J. Cheung, Monica M. N. Lee, Oscar G. W. Wong, Kenneth K. W. Li

    Published 2017-01-01
    “…Inclusion criteria include cataract surgery naïve patients undergoing phacoemulsification under local anaesthesia. …”
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  15. 615

    Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

    Published 2025-03-01
    “…Four machine learning algorithms—Random Forests, Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—were applied alongside a traditional logistic regression model. …”
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  16. 616

    A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

    Published 2025-02-01
    “…This research investigates three approaches for classifying skin cancer images. (1) Utilizing three fine-tuned pre-trained networks (VGG19, ResNet18, and MobileNet_V2) as classifiers. (2) Employing three pre-trained networks (ResNet-18, VGG19, and MobileNet v2) as feature extractors in conjunction with four machine learning classifiers (SVM, DT, Naïve Bayes, and KNN). (3) Utilizing a combination of the aforementioned pre-trained networks as feature extractors in conjunction with same machine learning classifiers. …”
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  17. 617

    A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens by Gina Bouchard, Weiruo Zhang, Ilayda Ilerten, Irene Li, Asmita Bhattacharya, Yuanyuan Li, Winston Trope, Joseph B. Shrager, Calvin Kuo, Michael G. Ozawa, Amato J. Giaccia, Lu Tian, Sylvia K. Plevritis

    Published 2025-02-01
    “…Intriguingly, drug-perturbation studies identify drug-induced spatial rearrangements that also appear in treatment-naïve human tumor samples, suggesting potential directions for characterizing spatial (re)-organization related to drug resistance. …”
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  18. 618

    Correction of Hypothyroidism Seems to Have No Effect on Body Fat by Okan Bakiner, Emre Bozkirli, Emine Duygu Ersozlu Bozkirli, Kursat Ozsahin

    Published 2013-01-01
    “…Methods. Forty-two women with naive autoimmune hypothyroidism were included. Also, 40 healthy participants were enrolled as a control group. …”
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  19. 619

    Use of a Ray-Based Reconstruction Algorithm to Accurately Quantify Preclinical MicroSPECT Images by Bert Vandeghinste, Roel Van Holen, Christian Vanhove, Filip De Vos, Stefaan Vandenberghe, Steven Staelens

    Published 2014-06-01
    “…The in vivo quantification error was determined for two radiotracers: [ 99m Tc]DMSA in naive mice ( n = 10 kidneys) and [ 111 In]octreotide in mice ( n = 6) inoculated with a xenograft neuroendocrine tumor (NCI-H727). …”
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  20. 620

    Predict Diabetes Using Voting Classifier and Hyper Tuning Technique by Chra Ali Kamal, Manal Ali Atiyah

    Published 2023-01-01
    “…Then six different algorithms (Logistic Regression, Decision Tree, Random Forest, K-nearest neighbor, Support Vector Machine and Naïve Bayes) were applied. In the second phase, the four best performed algorithms (with best estimated parameters for each of them) were chosen and used as an input for the voting classifier, because it applies to find the best algorithm between a group of multiple options.  …”
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